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Background: Secondary prevention after percutaneous coronary interventions (PCIs) is still challenging and lipoprotein(a) [Lp(a)] is believed to be a residual risk factor in this setting. However, the effect of Lp(a) in case of well-controlled low-density lipoprotein cholesterol (LDL-C) is still unclear. The interaction between Lp(a) and LDL-C has been studied in primary prevention but still needs to be investigated in secondary prevention. Hypothesis: Achieving adequate LDL-C control after PCI may reduce the cardiovascular (CV) risk associated with Lp(a). Methods: A retrospective study of consecutive patients who underwent PCI and reached their LDL-C target levels (<70mg/dL) at three academic centers sites between 2006 and 2017. All included patients must have an Lp(a) measurement before the PCI intervention. Clinical outcomes on 10-year follow-up were collected by reviewing the electronic patients' records. The primary outcomes included all-cause mortality (ACM) and major adverse CV events (MACE) including non-fatal MI, ischemic stroke, coronary revascularization, and CV death. Kaplan-Meier curves were created to compare the survival probabilities among patients with high Lp(a) (≥50mg/dL) versus those with low Lp(a) (<50mg/dL). Univariate and multivariate Cox regression analyses were performed to quantify the association of elevated Lp(a) with outcomes and control for potential confounders. Results: In total, 878 patients (median age = 68 years, 74% males) were included in the analysis. Of them, 242 (27.6%) had high Lp(a) ≥50mg/dL. Kaplan Meier analyses did not reveal any significant difference in survival probabilities across the Lp(a) groups for any of the outcomes (Figure 1). The results were consistent in univariate (MACE, HR: 1.08 [95%CIs 0.85-1.35]; ACM, HR: 0.97 [95% CI 0.76-1.23]) and multivariate analyses (MACE, HR: 1.14, [95% CIs 0.90-1.45]; ACM, HR: 1.08 [95% CI 0.84-1.39]). Conclusion: These findings suggest that, in patients who underwent PCI and achieved an LDL-C target of <70 mg/dL, elevated Lp(a) levels were not associated with and increased risk of MACE or mortality. Controlling the LDL-C should still be the cornerstone in secondary prevention after PCI, however, larger prospective studies are still warranted to validate our results.

Background: Myocarditis is a dreaded complication of immune-checkpoint inhibitor (ICI) therapy but challenging to diagnose. There are no published data comparing the two leading diagnostic criteria for ICI myocarditis and their association with cardiovascular events. Methods: Patients treated with ICI and cardiac Troponin (cTnT) measurements thereafter at a tertiary institution from 2011 to 2022 were identified. Charts were reviewed for ICI-related myocarditis according to the Bonaca et. al criteria and the ESC-ICOS guideline criteria. A propensity matched control group was identified of patients treated with ICI but without developing myocarditis. Medical records were reviewed for baseline characteristics and long-term outcomes, including cardiac death, MACE (myocardial infarction, TIA/stroke, new heart failure diagnosis), and arrhythmias (V-tach, A-fib, complete heart block). Results: A total of 59 patients were identified as having a diagnosis of ICI-related myocarditis per Bonaca criteria (16 having definite, 13 probable and 30 possible myocarditis), and 47 met the ESC-ICOS guideline criteria. Mean age was 73.1±10.2 years, 60.1% were male, median follow-up was 2.5 years. ICI-related myocarditis as diagnosed by both diagnostic criteria had prognostic value for cardiac death (HR 13.94, 95%CI 1.84-105.64, p=0.011 per Bonaca, HR 6.22, 95%CI 1.77-21.88, p=0.004 per ESC-ICOS), MACE, (HR 3.17, 95%CI 1.34-7.47, p=0.008 per Bonaca, HR 2.97, 95%CI 1.37-6.45, p=0.006 per ESC-ICOS), and arrhythmias (HR 1.93, 95%CI 1.10-3.38, p=0.022 per Bonaca, HR 2.09, 95%CI 1.21-3.60, p<0.001 per ESC-ICOS), (Figures 1 and 2). There was no significant difference for cardiac death (AUC 0.75 for Bonaca, AUC 0.74 for ESC, p=0.765) or MACE (AUC 0.66 for Bonaca, AUC 0.66 for ESC, p=0.916) when both criteria were compared with each other. Conclusion: The ESC-ICOS criteria were more restrictive than the Bonaca criteria for the diagnosis of ICI-related myocarditis but similar in terms of prognostic value.

Background: Catheter ablation (CA) is an effective treatment for atrial fibrillation (AF), but many patients experience recurrence post-intervention. Evaluating left atrial strain (LAS) to measure LA reservoir strain (LASr), conduit strain (LAScd), and contractile strain (LASct) could help predict AF recurrence, especially in patients with no evident signs of severe LA myopathy. Goal: This study aims to assess the prognostic value of pre-ablation LAS in both paroxysmal AF (paAF) and persistent AF(peAF) in patients with no evident signs of severe LA myopathy. Methods: This retrospective study encompassed AF patients who underwent their first CA procedure at Mayo Clinic Arizona from October 2018 to February 2022 and had a LAVI <40 ml/m2 and LVEF >55%. Transthoracic echocardiography parameters, including the three LAS phases, were collected using TOMTEC software on the closest date before the CA procedure. Receiver operating characteristic (ROC) curve analysis was used to evaluate the capability of LAS to detect patients with AF recurrence after CA from those without recurrence. Results: Out of 335 AF patients who underwent CA during the study period, 40 cases had LAVI <40 ml/m2 and LVEF >55% (72.5% male; mean age 69.2 ± 8 years). Of these, 15% (6/40) experienced recurrence, while 85% (34/40) maintained sinus rhythm. The mean values of LASr, LAScd, and LASct for all patients were 16.82, 11.23, and 6.87, respectively. ROC analysis indicated that the area under the curve (AUC) for LASr, LAScd, and LASct was 0.582, 0.502, and 0.710, respectively. (Graph 1A, Table 1A) LASct was the only parameter associated with AF recurrence (AUC: 0.71). Additionally, we developed a novel marker termed LAVI-LASct by combining LAVI and LASct values, which demonstrated improved discrimination with an ROC value of 0.74 (Graph 1B). Conclusions: LASct demonstrated predictive capability for AF recurrence in patients with no severe LA dilation and preserved LVEF, potentially due to its ability to detect early atrial dysfunction preceding visible structural changes or myocardial pathology. The addition of LAVI values provided better discrimination for the ROC model. Further research is needed to confirm the clinical relevance of LAS in AF patients undergoing ablation.

Background: New-onset atrial fibrillation (AF) is common among kidney transplant (KTx) recipients and is associated with reduced patient survival. Predictors of AF after KTx are not well understood, although AF can be associated with traditional and non-traditional risk factors. While artificial intelligence-enabled electrocardiography (AI-ECG) has shown promise in predicting incident AF, its predictive and prognostic implications in the KTx population have not yet been evaluated. Hypothesis: AI-ECG can predict new-onset AF and carries prognostic implications in patients undergoing KTx. Aims: To evaluate the clinical implications of applying AI-ECG to the preoperative ECGs of recipients of a KTx. Methods: Patients without a history of AF who underwent KTx at three referral centers between 2011 and 2021, with at least one preoperative ECG, were included in this retrospective study. Preoperative ECGs were analyzed using a previously developed AI-ECG algorithm to estimate the probabilities of new-onset AF. Based on these probabilities, patients were categorized into two groups: high and low probability of incident AF. The optimal cut-off value for the AI-ECG tool was determined using ROC analysis. The incidence of new-onset AF and mortality at 5 years post KTx were compared between these two groups using univariate and multivariate Cox regression analyses. Results: In total, 6246 patients were included (mean age 52.9 ±14.3 years, 58.7% males). A pre-transplant AI-ECG probability of AF >10% was identified as the most accurate cutoff point to distinguish between patients at low risk and high risk of incident AF (ROC = 0.72). The study found that a preoperative AI-ECG high risk of AF demonstrated not only a strong association with new-onset AF (HR 2.54, 95%CI 2.02-3.19, p<0.001 on multivariable analysis, Figure 1A ) but was also associated with an increased risk of mortality both on univariate (HR 2.73, 95%CI 2.34-3.18, p<0.001) and multivariate (HR 1.57, 95%CI 1.29-1.91, p<0.001 ) analysis at 5-year follow-up ( Figure 1B ). Conclusion: The application of AI-ECG to a single widely available test may help assess the risk of new-onset AF and mortality in patients undergoing KTx. Accurate risk stratification may identify a high-risk subgroup of transplant recipients who can benefit from closer AF monitoring, risk factor modification, and early management.

The assessment of left atrial strain (LAS) has emerged as an essential component in the evaluation of cardiac function, especially in pathologies such as heart failure and atrial fibrillation. This narrative review aims to outline the available methods for assessing LAS with a major emphasis on speckle-tracking echocardiography techniques. Other imaging modalities, including cardiac magnetic resonance and cardiac computed tomography, also provide important information on LA dynamics but have disadvantages with respect to cost and availability. The current narrative review underlines basic concepts such as the accurate assessment of LAS and discusses the clinical relevance of LAS by pointing out its significant diagnostic and prognostic role in several cardiovascular conditions. The aim of this article is to discuss the current integration of LAS into clinical practice with a view to further improving patient management and treatment strategies.

Background/Objectives: Pectus excavatum (PEx) is considered, at least partially, a familial disorder. A variety of inheritance patterns, associations with genetic syndromes, and pathogenic variants have been reported. However, the etiology of this condition is still not completely understood, and no known genes have been identified as definitive contributors. Methods: Family members with a confirmed PEx diagnosis (one proband and two first-degree relatives) and non-affected members were recruited into this study. Exome sequencing was performed on all affected familial PEx cases to systematically screen for candidate genes that are likely to be causative for PEx, and on non-affected family members for variant segregation analysis. Results: Ten families, with three affected members each, participated, providing thirty familial PEx cases. Different inheritance patterns were represented across the ten pedigrees, with possible incomplete penetrance. Genetic variants in REST (essential for neuronal development and associated with pectus deformities in prior studies), SMAD4 (variants can predispose individuals to thoracic aortic diseases), and COL5A (associated with Ehlers–Danlos syndrome and Fibromuscular dysplasia) were initially identified as potentially linked to the development of pectus deformities and segregated with the phenotype. No variants were shared across families in the studied population. Conclusions: Germline exome sequencing of families with multiple individuals affected by PEx in our study identified potential gene candidates linked to PEx. These candidates are private to individual families and no strong candidates shared across multiple families were identified. These findings suggest that the inheritance of PEx may not be strongly related to a shared single genetic variant in known genes. Given the accumulating evidence for the genetic basis of familial PEx, further studies, including polygenic analyses, as well as assessment of the non-coding genome and possible epigenetic markers are warranted.

Abstract Aims Lipoprotein(a) (Lp(a)) levels are known to be mainly genetically determined. However, only scarce data are available on the intra-individual variability of Lp(a) levels across time. Methods and results We included adult patients (≥18 years old) who had baseline and follow-up Lp(a) measurements (between 1997 and 2024) with a minimum of 1 year apart. Patients were categorized into three groups as follows: normal (&lt;30 mg/dL), borderline (30 to 50 mg/dL), and high Lp(a) (≥50 mg/dL). Multivariable logistic regression was conducted to assess the predictors of the intra-individual changes in Lp(a) ≥ 10 mg/dL. A total of 11 669 individuals (median age: 54 years, 60% males) were included in our analysis, with median time between measurements of 4.5 years [interquartile range (IQR): 2.2, 10.6]. The median Lp(a) was 16 mg/dL (IQR: 7, 52) at baseline, compared with 15 mg/dL (IQR: 7, 52) at follow-up. At follow-up, 96.4% of individuals with normal Lp(a) and 89.9% with high Lp(a) remained in their categories, while 51.2% with borderline Lp(a) changed their category. Of the included population, 24.9% had an intra-individual Lp(a) change ≥ 10 mg/dL. Female sex (P &lt; 0.001), history of ASCVD (P = 0.003), statin therapy (P = 0.003), and elevated LDL cholesterol (LDL-C) levels ≥ 100 mg/dL (P &lt; 0.001) were significantly associated with higher odds of intra-individual Lp(a) changes ≥ 10 mg/dL. Conclusion Lipoprotein(a) levels were generally stable over time; however, patients with borderline levels may require more than one Lp(a) measurement, especially if they are females, have a history of ASCVD, have elevated LDL-C levels, or are on statin therapy.

Lipoprotein (a) is a complex lipid molecule that has sparked immense interest in recent years, after studies demonstrated its significant association with several cardiovascular conditions. Lp(a) promotes cardiovascular disease through its combined proatherogenic, pro-inflammatory, and prothrombotic effects. While the measurement of Lp(a) has become widely available, effective methods to reduce its concentration are currently limited. However, emerging data from ongoing clinical trials involving antisense oligonucleotides have indicated promising outcomes in effectively reducing Lp(a) concentrations. This may serve as a potential therapeutic target in the management and prevention of myocardial infarction, calcific aortic stenosis, and cerebrovascular accidents. In contrast, the role of Lp(a) in atrial fibrillation, in-stent restenosis, cardiac allograft vasculopathy, and bioprosthetic aortic valve degeneration remains unclear. This review article aims to thoroughly review the existing literature and provide an updated overview of the evidence surrounding the association of Lp(a) and these cardiovascular diseases. We seek to highlight controversies in the existing literature and offer directions for future investigations to better understand Lp(a)’s precise role in these conditions, while providing a summary of its unique molecular characteristics.